Has a Higgs-flavon with a 750750 GeV mass been detected at the LHC13?

Higgs-flavon fields appear as a part of the Froggatt-Nielsen (FN) mechanism, which attempts to explain the hierarchy of Yukawa couplings. We explore the possibility that the 750 GeV diphoton resonance recently reported at the LHC13, could be identified with a low-scale Higgs-flavon field $H_F$ and find the region of the parameter space consistent with CMS and ATLAS data. It is found that the extra vector-like fermions of the ultraviolet completion of the FN mechanism are necessary in order to reproduce the observed signal. We consider a standard model (SM) extension that contains two Higgs doublets (a standard one and an inert one) and one complex FN singlet. The inert doublet includes a stable neutral boson, which provides a viable dark matter candidate, while the mixing of the standard doublet and the FN singlet induces flavor violation in the Higgs sector at the tree-level. Constraints on the parameters of the model are derived from the LHC Higgs data, which include the search for the lepton flavor violating decay of the SM Higgs boson $h\to \bar{\mu}\tau$. It is also found that in some region of the parameter space the model may give rise to a large branching ratio for the $H_F \to hh$ decay, of the order of 0.1, which could be searched for at the LHC.Comment: 18 pages, 7 Figures, includes updated files to match published versio

The uses of post-editing in the subtitling classroom: What do subtitlers-to-be say?

In recent years, an increasing number of scholars have attempted to gain a better understanding of the technological advancements and innovation that are gaining momentum in the audiovisual translation (AVT) industry (Díaz-Cintas and Massidda, 2019). We live surrounded by screens and have become avid consumers of audiovisual content (Nikolic and Bywood, 2021), particularly led by streaming platforms and the internetisation of society (Lobato, 2018). Technology has also altered industry workflows and translators’ workstations and habits. A wider integration of cloud technologies in AVT localisation has taken place (Bolaños-García-Escribano and Díaz-Cintas, 2020), and computer-assisted technologies, such as machine translation and translation memory, which were often neglected in our field, have also gained greater currency (Burchardt et al., 2016). Machine translation engines are operating in cloud-based subtitling systems (Mehta et al., 2020), which are offering features that allow for machine-translated subtitles from pre-spotted templates and integrate automatic speech recognition to further automatise the spotting of subtitles. As discussed by Georgakopoulou and Bywood (2014) and Bywood et al. (2017), this has led to a rise in the profile of the post-editor in AVT, and more specifically subtitling. I will discuss two educational experiences in which subtitlers-to-be were required to post-edit subtitled audiovisual material in both English and Spanish. In the first experience, an international team of eight translation trainees post-edited raw automatic subtitles for educational videos following a project-based approach. The second experience (2021) was a practical experiment involving master-level students of subtitling who localised a video clip using a commercial cloud-based subtitling system; it involved a control group and another two groups that did not use machine translation. The feedback collated after each experience through online questionnaires has proved paramount to further justify the need to embed subtitle post-editing in the AVT curriculum. The purpose of this study is to ultimately identify bottlenecks as well as good practices in pedagogical subtitle post-editing

Detecting Hands in Egocentric Videos: Towards Action Recognition

Recently, there has been a growing interest in analyzing human daily activities from data collected by wearable cameras. Since the hands are involved in a vast set of daily tasks, detecting hands in egocentric images is an important step towards the recognition of a variety of egocentric actions. However, besides extreme illumination changes in egocentric images, hand detection is not a trivial task because of the intrinsic large variability of hand appearance. We propose a hand detector that exploits skin modeling for fast hand proposal generation and Convolutional Neural Networks for hand recognition. We tested our method on UNIGE-HANDS dataset and we showed that the proposed approach achieves competitive hand detection results

Assessment of the importance of the current-wave coupling in the shelf ocean forecasts

International audienceThe effects of wave-current interactions on shelf ocean forecasts is investigated in the framework of the MFSTEP (Mediterranean Forecasting System Project Towards Enviromental Predictions) project. A one way sequential coupling approach is adopted to link the wave model (WAM) to the circulation model (SYMPHONIE). The coupling of waves and currents has been done considering four main processes: wave refraction due to currents, surface wind drag and bottom drag modifications due to waves, and the wave induced mass flux. The coupled modelling system is implemented in the southern Catalan shelf (NW Mediterranean), a region with characteristics similar to most of the Mediterranean shelves. The sensitivity experiments are run in a typical operational configuration. The wave refraction by currents seems to be not very relevant in a microtidal context such as the western Mediterranean. The main effect of waves on current forecasts is through the modification of the wind drag. The Stokes drift also plays a significant role due to its spatial and temporal characteristics. Finally, the enhanced bottom friction is just noticeable in the inner shelf